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The use of low temperature combustion (LTC) modes has demonstrated abilities to lower diesel engine emissions while maintaining good fuel consumption. LTC is assumed to be a viable solution to assist in meeting stringent upcoming diesel engine emissions targets, particularly nitric oxides (NOx) and particulate matter (PM). However, LTC is currently limited to low engine loads and is not a feasible solution at higher loads on production engines. A mixed mode combustion strategy must be implemented to take advantage of the benefits offered from LTC at the low loads and speeds while switching to a conventional diesel combustion strategy at higher loads and speeds and thus allowing full range use of the engine under realistic driving conditions. Experiments were performed to characterize engine out emissions during transient engine operating conditions involving LTC combustion strategies.

Two advanced combustion models have been validated with the KIVA-3V Release 2 code in the context of two-stage combustion in a heavy duty diesel engine. The first model uses CHEMKIN to directly integrate chemistry in each computational cell. The second model accounts for flame propagation with the G-equation, and CHEMKIN predicts autoignition and handles chemistry ahead of and behind the flame front. A Damköhler number criterion was used in flame containing cells to characterize the local mixing status and determine whether heat release and species change should be a result of flame propagation or volumetric heat release. The purpose of this criterion is to make use of physical and chemical time scales to determine the most appropriate chemistry model, depending on the mixture composition and thermodynamic properties of the gas in each computational cell.

In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

Homogeneous Charge Compression Ignition (HCCI) combustion is being considered as a practical solution for diesel engines due to its high efficiency and low NOx and PM emissions. However, for diesel HCCI operation, there are still several problems that need to be solved. One is the spay-wall impingement issue associated with early injection, and a further problem is the extension of HCCI operation from low load to higher engine loads. In this study, a combination of Adaptive Injection Strategies (AIS) and a Two-Stage Combustion (TSC) strategy are proposed to solve the aforementioned problems. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN-GA code, was employed in this study, where Genetic Algorithms (GA) were used to optimize heavy-duty diesel engine operating parameters. The TSC concept was applied to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load).

1 An all fiber-optic sensor has been developed to measure H2O mole fraction and gas temperature in an HCCI engine. This absorption-spectroscopy-based sensor utilizes a broad wavelength (1320 to 1380 nm) source (supercontinua generated by a microchip laser) and a series of fiber Bragg gratings (19 gratings centered on unique water absorption peaks) to track the formation and temperature of combustion water vapor. The spectral coverage of the system promises improved measurement accuracy over two-line diode-laser based systems. Meanwhile, the simplicity of the fiber Bragg grating chromatic dispersion approach significantly reduces the data reduction time and cost relative to previous supercontinuum-based sensors. The data provided by the system is expected to enhance studies of the chemical kinetics which govern HCCI ignition as well as HCCI modeling efforts.

The effects of residual gas mixing were studied in a single-cylinder, air-cooled utility engine using both external exhaust gas recirculation (EGR) and internal residual retention. EGR was introduced far upstream of the throttle to ensure proper mixing. Internal residual was changed by varying the length of the valve overlap period. EGR was measured in the intake system; the total in-cylinder diluent was directly measured using a skip-fire, cylinder dumping technique. A sweep of diluent fraction was performed at different engine speeds, engine loads, fuel mixture preparation systems, and ignition timings. An optimum level of diluent, where the combined hydrocarbon and NOx emissions were minimal, was found to exist for each operating condition. Higher levels of diluent, either through internal retention or external recirculation, caused the combined emissions to increase.

A comprehensive system level modeling approach is used to understand the effects of the various physical actuators during diesel HCCI transients. Control concepts during transient operations are simulated using a set of actuators suitable for combustion control in diesel HCCI engines (intake valve actuation, injection timing, cooled EGR, intake boost pressure and droplet size). The impact of these actuating techniques on the overall engine performance is quantified by investigating the amount of actuation required, timing of actuation and the use of a combination of actuators. Combined actuation improved actuation space that can be used to phase combustion timing better and in extending the operating range. The results from transient simulations indicate that diesel HCCI operation would benefit from the combined actuation of intake valve closure, injection timing, boost and cooled EGR.

Schlieren visualization was performed to investigate hydrogen injection into a quiescent chamber. The injection pressures investigated were 52 and 104 bar, and the chamber density ranged from 1.15 to 12.8 kg/m3, giving rise to underexpanded jets for all conditions. The expansion waves outside the nozzle were clearly visible with hydrogen, and the effect was confirmed with studies of nitrogen injected into a nitrogen environment. The distance between the expansion wave fronts was found to scale directly with the ratio of the exit pressure to the chamber pressure. The jet tip penetration rate was measured and was found to increase with injection pressure, and decrease with chamber density as expected. A mass- and momentum-preserving scheme was developed to relate the underexpanded jet to a subsonic jet of larger diameter.

The heavy-duty diesel engine industry is required to meet stringent emission standards. There is also the demand for more fuel efficient engines by the customer. In a previous study on an engine with variable intake valve closure timing, the authors found that an early single injection and accompanying premixed charge compression ignition (PCCI) combustion provides advantages in emissions and fuel economy; however, unacceptably high peak pressures and rates of pressure-rise impose a severe operating constraint. The use of a Pressure Reactive Piston assembly (PRP) as a means to limit peak pressures is explored in the present work. The concept is applied to a heavy-duty diesel engine and genetic algorithms (GA) are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to provide an optimized set of operating variables.

A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN-GA code, was employed in this study, where Genetic Algorithms (GA) were used to optimize heavy-duty diesel engine operating parameters. A two-stage combustion (TSC) concept was explored to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load). Two combustion modes were combined in this concept. The first stage is ideally Homogeneous Charge Compression Ignition (HCCI) combustion and the second stage is diffusion combustion under high temperature and low oxygen concentration conditions. This can be achieved for example by optimization of two-stage combustion using multiple injection or sprays from two different injectors.

Transient engine tests were performed to investigate behavior of transient emissions--hydrocarbon (HC) and oxides of Nitrogen (NOx)--in a 2.4L turbocharged four cylinder High Speed Direct Injection (HSDI) diesel engine which is coupled to a hydrostatic transient dynamometer. Emissions were measured from one exhaust port 5 cm downstream of the exhaust valve and from the exhaust pipe 14 cm below the wastegate of the turbocharger. These measurements were made with fast response HC and NOx measurement analyzers. The experiments were conducted by increasing torque at constant speed and by increasing speed at constant torque, in conventional diesel combustion regions. The emissions from the two locations are compared. The transient effects of Exhaust Gas Recirculation (EGR) rates and injection timing on HC and NOx are described and the effects of linear and step load change on emissions are compared.

An overall diesel engine and aftertreatment system model has been created that integrates diesel engine, exhaust system, engine emissions, and diesel particulate filter (DPF) models using MATLAB Simulink. The 1-D engine and exhaust system models were developed using WAVE. The engine emissions model combines a phenomenological soot model with artificial neural networks to predict engine out soot emissions. Experimental data from a light-duty diesel engine was used to calibrate both the engine and engine emissions models. The DPF model predicts the behavior of a clean and particulate-loaded catalyzed wall-flow filter. Experimental data was used to validate this sub-model individually. Several model integration issues were identified and addressed. These included time-step selection, continuous vs. limited triggering of sub-models, and code structuring for simulation speed. Required time-steps for different sub models varied by orders of magnitude.

The strategy of variable Intake Valve Closure (IVC) timing, as a means to improve performance and emission characteristics, has gained much acceptance in gasoline engines; yet, it has not been explored extensively in diesel engines. In this study, genetic algorithms are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to investigate the optimum operating variables for a typical heavy-duty diesel engine working with late IVC. The effects of start-of-injection timing, injection duration and exhaust gas recirculation were investigated along with the intake valve closure timing. The results show that appreciable reductions in NOx+HC (∼82%), soot (∼48%) and BSFC (∼7.4%) are possible through this strategy, as compared to a baseline diesel case of (NOx+HC) = 9.48g/kW-hr, soot = 0.17 g/kW-hr and BSFC = 204 g-f/kW-hr. The additional consideration of double injections helps to reduce the high rates of pressure rise observed in a single injection scheme.

In this paper, optimized single and double injection schemes were found using multi-dimensional engine simulation software (KIVA-3V) and a micro-genetic algorithm for a heavy duty diesel engine. The engine operating condition considered was at 1737 rev/min and 57 % load. The engine simulation code was validated using an engine equipped with a hydraulic-electronically controlled unit injector (HEUI) system. Five important parameters were used for the optimization - boost pressure, EGR rate, start-of-injection timing, fraction of fuel in the first pulse and dwell angle between first and second pulses. The optimum results for the single injection scheme showed significant improvements for the soot and NOx emissions. The start of injection timing was found to be very early, which suggests HCCI-like combustion. Optimized soot and NOx emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively, for the single injection scheme.

Multi-dimensional computational efforts using comprehensive and skeletal kinetics have been made to investigate the cool flame region in HCCI combustion. The work was done in parallel to an experimental study that showed the impact of the negative temperature coefficient and the cool flame on the start of combustion using different fuels, which is now the focus of the simulation work. Experiments in a single cylinder CFR research engine with n-butane and a primary reference fuel with an octane number of 70 (PRF 70) were modeled. A comparison of the pressure and heat release traces of the experimental and computational results shows the difficulties in predicting the heat release in the cool flame region. The behavior of the driving radicals for two-stage ignition is studied and is compared to the behavior for a single-ignition from the literature. Model results show that PRF 70 exhibits more pronounced cool flame heat release than n-butane.

The effect of injection rate shape on spray evolution and emission characteristics is investigated and a methodology for active control of fuel injection is proposed. Extensive validation of advanced vaporization and primary jet breakup models was performed with experimental data before studying the effects of systematic changes of injection rate shape. Excellent agreement with the experiments was obtained for liquid and vapor penetration lengths, over a broad range of gas densities and temperatures. Also the predicted flame lift-off lengths of reacting diesel fuel sprays were in good agreement with the experiments. After the validation of the models, well-defined rate shapes were used to study the effect of injection rate shape on liquid and vapor penetration, flame lift-off lengths and emission characteristics.

A single cylinder CFR research engine has been run in HCCI combustion mode at the rich and the lean limits of the homogeneous charge operating range. To achieve a variation of the degree of charge stratification, two GDI injectors were installed: one was used for generating a homogeneous mixture in the intake system, and the other was mounted directly into the side of the combustion chamber. At the lean limit of the operating range, stratification showed a tremendous improvement in IMEP and emissions. At the rich limit, however, the stratification was limited by the high-pressure rise rate and high CO and NOx emissions. In this experiment the location of the DI injector was in such a position that the operating range that could be investigated was limited due to liquid fuel impingement onto the piston and liner.

A cylinder model was developed using artificial neural networks (ANN). The cylinder model utilized the trained ANN models to predict engine parameters including cylinder pressures, cylinder temperatures, cylinder wall heat transfer, NOx and soot emissions. The ANN models were trained to approximate CFD simulation results of an engine. The ANN cylinder model was then applied to predict engine performance and emissions over the standard heavy-duty FTP transient cycle. The engine responses varying over the engine speed and torque range were simulated in the course of the transient test cycle. It was demonstrated that the ANN cylinder model is capable of simulating the characteristics of the engine operating under transient conditions reasonably well.

The KIVA 3V code has been applied to predict combustion chamber heat flux in an air-cooled utility engine. The KIVA heat flux predictions were compared with experimentally measured data in the same engine over a wide range of operating conditions. The measured data were found to be approximately two times larger than the predicted results, which is attributed to the omission of chemical heat release in the near-wall region for the heat transfer model applied. Modifying the model with a simple scaling factor provided a good comparison with the measured data for the full range of engine load, heat flux sensor location, air-fuel ratio and spark timings tested. The detailed spatially resolved results of the KIVA predictions were then used to develop a simplified model of the combustion chamber temporally integrated heat flux using an artificial neural network (ANN).

A radiation model based on the Discrete Ordinates Method (DOM) was incorporated into the KIVA3v multidimensional code to study the effects of soot and radiation on diesel engine performance at high load. A thermophoretic soot deposition model was implemented to predict soot concentrations in the near-wall region, which was found to affect radiative heat flux levels. Realistic, non-uniform combustion chamber wall surface temperature distributions were predicted using a finite-element-based heat conduction model for the engine metal components that was coupled with KIVA3v in an iterative scheme. The more accurate combustion chamber wall temperatures enhanced the accuracy of both the radiation and soot deposition models as well as the convective heat transfer model. For a basline case, (1500 rev/min, 100% load) it was found that radiation can account for as much as 30% of the total wall heat loss and that soot deposition in each cycle is less than 3% of the total in-cylinder soot.